Measuring knowledge worker productivity: A taxonomy

Journal of Intellectual Capital

Volumn 5, Issue 4, 2004, Pages 602-628

  Ramírez, Yuri W ^a   Nembhard, David A ^b  

^a UNIVERSITY OF WISCONSIN MADISON   (United States)

^b PENNSYLVANIA STATE UNIVERSITY   (United States)

Author keywords

Employee productivity; Knowledge organizations; Performance measures; Quality

Indexed keywords

EID: 84986116693     PISSN: 14691930     EISSN: 1758468     Source Type: Journal    
DOI: 10.1108/14691930410567040     Document Type: Article

References (62)

1. Agarwall, S.C. (1980), “A study of productivity measures for improving benefit-cost ratios of operating organizations”, International Journal of Production Research, Vol. 18 No. 1, pp. 83-102.
2. Ahmed, P.K., Lim, K.K. and Zairi, M. (1999), “Measurement practice for knowledge management”, Journal of Workplace Learning: Employee Counselling Today, Vol. 11 No. 8, pp. 304-11.
3. Berglind, B.L. and Scales, C.D. (1987), “White-collar productivity: seeing through the camouflage”, Management Review, Vol. 76 No. 6, pp. 41-7.
4. Bock, D. and Klepper, R. (1992), “FP-S: a simplified function point counting method”, Journal of Systems and Software, Vol. 18 No. 3, pp. 245-54.
5. Bok, H.S. and Raman, K.S. (2000), “Software engineering productivity measurement using function points: a case study”, Journal of Information Technology, Vol. 15 No. 1, pp. 79-101.
6. Bridges, B.M. (1992), “Using operational audit to measure white collar productivity”, paper presented at Productivity and Quality Improvement in Government Conference, February.
7. Brisley, C.L. and Fielder, W.F.F. Jr (1983), “Unmeasurable output of knowledge/office workers can and must be measured”, Industrial Engineering, Vol. 15 No. 7, pp. 42-7.
8. Bumbarger, W.B. (1984), Operation Function Analysis: Do it Yourself Productivity Improvement, Van Nostrand Reinhold, New York, NY.
9. Charnes, A., Cooper, W. and Rhodes, E. (1978), “Measuring the efficiency of decision-making units”, European Journal of Operational Research, Vol. 2 No. 6, pp. 429-44.
10. Charnes, A., Cooper, W., Lewin, A. and Seiford, L. (1994), Data Envelopment Analysis: Theory, Methodology and Application, Kluwer Academic Publishers, Boston, MA.
11. Christopher, W.F. (1984), “How to measure and improve the productivity in professional, administrative, and service organizations”, Annual International IE Conference, Norcross, GA.
12. Clark, K.B. and Wheelwright, S.C. (1993), Managing New Product and Process Development: Text and Cases, Harvard Business School, Free Press, New York, NY, pp. 240-5.
13. Coates, J. (1986), “Three models for white collar productivity improvement”, Industrial Management, Vol. 28 No. 2, pp. 7-14.
14. Cote, V., Brurgue, P., Oligny, S. and Rivard, N. (1988), “Software metrics: an overview of recent results”, Journal of Systems and Software, Vol. 8 No. 2, pp. 121-31.
15. Davenport, T. (2002), “Can you boost knowledge work's impact on the bottom line?”, Management Update, Vol. 7 No. 11, pp. 3-5.
16. Davenport, T. and Prusak, L. (2000), Working Knowledge: How Organizations Manage What They Know, Harvard Business School Press, Boston, MA.
17. Davenport, T., Thomas, R. and Cantrell, S. (2002), “The mysterious art and science of knowledge-worker performance”, MIT Sloan Management Review, Vol. 44 No. 1, pp. 23-9.
18. Davis, T. (1991), “Information technology and white-collar productivity”, Academy of Management Executive, Vol. 5 No. 1, pp. 55-68.
19. Dove, R. (1998), “The knowledge worker”, Automotive Manufacturing & Production, Vol. 110 No. 6, pp. 26-28.
20. Dreger, B. (1989), Function Point Analysis, Prentice-Hall, Englewood Cliffs, NJ.
21. Drucker, P. (1959), The Landmarks of Tomorrow, Harper & Row, New York, NY.
22. Drucker, P. (1968), The Practice of Management, Pan, London.
23. Drucker, P. (1988), “The coming of the new organization”, Harvard Business Review, Vol. 66 No. 1, pp. 45-53.
24. Drucker, P. (1991), “The new productivity challenge”, Harvard Business Review, Vol. 69 No. 6, pp. 69-80.
25. Drucker, P. (1993), Post-Capitalist Society, HarperBusiness, New York, NY.
26. Drucker, P. (1994), Adventures of a Bystander, Transaction Publishers, New Brunswick, NJ.
27. Drucker, P. (1999), “Knowledge-worker productivity: the biggest challenge”, California Management Review, Vol. 41 No. 2, pp. 79-85.
28. Fitz-Enz, J. (1986), “White-collar effectiveness: Part I: the employees’ side”, Management Review, Vol. 75 No. 5, pp. 52-5.
29. Gordon, G.E. (1997), “The last word on productivity and telecommuting”, available at: www.gilgordon.com/downloads/productivity.txt (accessed 2002).
30. Green, R.G. and Secret, M. (1996), “Publishing by social work scholars in social work and non-social work journals”, Social Work Research, Vol. 20 No. 1, pp. 31-42.
31. Greenberg, E. (1986), “Measuring white-collar productivity”, Management Review, Vol. 75 No. 9, pp. 65-7.
32. Gummer, B. (2000), “Managing knowledge and knowledge workers in organizations: when you got it, flaunt it!”, Administration in Social Work, Vol. 24 No. 4, p. 75.
33. Harris, M.F. and Vining, W. (1987), “The IE's future role in improving knowledge worker productivity”, Industrial Engineering, Vol. 19 No. 7, pp. 28-32.
34. Helton, R. (1988), “The ‘best work’ method of knowledge worker assessment”, Industrial Management, Vol. 30 No. 5, pp. 19-22.
35. Horvath, D. (2001), “Knowledge worker definition”, Search CRM Technical Dictionary by Tech Target, available at: http://searchcrm.techtarget.com/sDefinition/0,sid11_gci212450,00.html (accessed 2002).
36. Huang, S., Dismukes, J., Shi, J., Su, Q., Razzak, M., Bodhale, R. and Robinson, D.E. (2003), “Manufacturing productivity improvement using effectiveness metrics and simulation analysis”, International Journal of Production Research, Vol. 41 No. 3, p. 513.
37. Jablonski, M. and Kunze, K. (1990), “Hours at work: a new base for BLS productivity statistics”, Monthly Labor Review, Vol. 113 No. 2, p. 17.
38. Janz, B.D., Colquitt, J.A. and Noe, R.A. (1997), “Knowledge worker team effectiveness: the role of autonomy, interdependence, team development, and contextual support variables”, Personnel Psychology, Vol. 50 No. 4, pp. 877-902.
39. Klassen, K.J., Russell, R.M. and Chrisman, J.J. (1998), “Efficiency and productivity measures for high contact services”, Service Industries Journal, Vol. 18 No. 4, pp. 1-19.
40. Matson, J., Barrett, B. and Mellichamp, J. (1994), “Software development cost estimation using function points”, IEEE Transactions on Software Engineering, Vol. 20 No. 4, pp. 275-87.
41. Merrifield, B. (1994), “Measurements of productivity: key to survival”, International Journal of Technology Management, Vol. 9 No. 5-7, pp. 771-84.
42. Montgomery, D. (1997), Introduction to Statistical Quality Control, Wiley, New York, NY.
43. Mundel, M.E. (1975), Measuring and Enhancing the Productivity of Service and Government Organizations, Asian Productivity Organization, Tokyo.
44. Naisbitt, J. (1982), Megatrends, Warner Books, New York, NY.
45. Nickols, F. (2000), “‘What is’ in the world of work and working: some implications of the shift to knowledge work”, Butterworth-Heinemann Yearbook of Knowledge Management, pp. 1-7, also available at: http://home.att.net/∼nickols/shifts.htm.
46. Overby, M. (1983), “Technique for group time measurement simplifies indirect labor observations”, Industrial Engineering, Vol. 15 No. 7, pp. 34-40.
47. Paradi, J.C., Smith, S. and Schaffnit-Chatterjee, C. (2002), “Knowledge worker performance analysis using DEA: an application to engineering design teams at Bell Canada”, IEEE Transactions on Engineering Management, Vol. 49 No. 2, p. 161.
48. Pepitone, J.S. (2002), “A case for humaneering”, IIE Solutions, Vol. 34 No. 5, pp. 39-44.
49. Picard, R.G. (1998), “Measuring and interpreting productivity of journalists”, Newspaper Research Journal, Vol. 19 No. 4, pp. 71-80.
50. Pressman, R. (1987), Software Engineering, McGraw-Hill, New York, NY.
51. Ray, P.K. and Sahu, S. (1989), “The measurement and evaluation of white-collar productivity”, International Journal of Operations & Production Management, Vol. 9 No. 4, pp. 28-48.
52. Schroeder, R., Anderson, J. and Scudder, G. (1985), “Measurement of white collar productivity”, International Journal of Operations & Production Management, Vol. 5 No. 2, pp. 25-33.
53. Sink, S. (1985), Productivity Management: Planning, Measurement and Evaluation, Control and Improvement, John Wiley & Sons, New York, NY.
54. Smith, C. (1984), “Awareness, analysis and improvement are keys to white collar productivity”, Industrial Engineering, Vol. 16 No. 1, pp. 82-6.
55. Taylor, F. (1911), The Principles of Scientific Management, Harper & Brothers, New York, NY.
56. Thomas, B.E. and Baron, J.P. (1994), “Evaluating knowledge worker productivity: literature review”, Interim Report, No. FF-94/27, USACERL, pp. 1-27, available at: www.cecer.army.mil/kws/tho_lit.htm#abs.
57. Thompson, P., Warhurst, C. and Callaghan, G. (2001), “Ignorant theory and knowledgeable workers: interrogating the connections between knowledge, skills and services”, Journal of Management Studies, Vol. 38 No. 7, pp. 923-43.
58. Tjosvold, D. (1986), Working Together to Get Things Done: Managing for Organizational Productivity, Lexington Books, Lexington, MA.
59. Wrigley, C. and Dexter, A. (1991), “A model for measuring information system size”, MIS Quarterly, Vol. 15 No. 2, pp. 245-57.
60. Yellowlees, R.A. (1986), “White collar productivity – the technology challenge”, Industrial Management, Vol. 28 No. 2, pp. 14-17.
61. Zigon, J. (1998), “How to measure white collar employee productivity”, ZPG, Resources for Measuring, Managing and Improving Employee Performance, available at: www.zigonperf.com/articles/whitecollar.html (accessed 2003).
62. Grochow, J.M. (1999), “Productivity and the IT personnel shortage”, PC Week, Vol. 16 No. 34, p. 78.